Efficient mining of frequent sequence generators

Sequential pattern mining has raised great interest in data mining research field in recent years. However, to our best knowledge, no existing work studies the problem of frequent sequence generator mining. In this paper we present a novel algorithm, FEAT (abbr. Frequent sEquence generATor miner), to perform this task. Experimental results show that FEAT is more efficient than traditional sequential pattern mining algorithms but generates more concise result set, and is very effective for classifying Web product reviews. Categories and Subject Descriptors: H.2.8 [Database Management]: Database applications - Data Mining General Terms: Algorithms, Performance

• Type: Conference
• Year: 2008
• Where: WWW
• Authors: Chuancong Gao, Jianyong Wang, Yukai He, Lizhu Zhou
• Keywords: Internet Technology, Pattern Mining Algorithms, Sequence Generator Mining, Sequential Pattern Mining, WWW 2008